CIKM Topic Selection

CIKM Topic Selection

CIKM is the room where three communities meet: information retrieval, data mining, and knowledge management with its database roots. Its sponsorship tells the story — ACM SIGIR (since 1993) plus SIGWEB (since 2006) — and its 2026 self-description spans information access, knowledge representation, data integration, and personalization (source map, checked 2026-07-08). Fit questions here are therefore different from single-community venues: the issue is rarely "is this in scope" and usually "is the breadth an advantage for this particular paper."

The tri-community fit question

Ask which communities the paper genuinely speaks to, then count:

• Two or three lanes — a retrieval model built on a knowledge graph, a mining method whose output feeds a search or QA system, an entity-resolution pipeline with both database and IR evaluation. This is the CIKM sweet spot: the blended reviewer pool is an asset, because no single-community venue gives all lanes credit.
• Exactly one lane, done deeply — pure ranking-model work, pure pattern-mining theory, pure query optimization. CIKM accepts such papers, but the specialist venue (SIGIR, KDD, SIGMOD/VLDB) usually offers sharper reviewers and more career signal. Choose CIKM deliberately, e.g., for the calendar, not by default.
• Zero lanes — contributions about model architecture, vision, or generic NLP with an incidental retrieval experiment. Reframe or reroute; scope-mismatch reads fast at a venue whose name states its scope.

Honest calendar positioning

CIKM's May deadline and November meeting make it the information family's fall harvest: work that missed or matured past SIGIR's January gate, KDD's February cycle-2 gate, or that wants a decision before WSDM's August gate. Using CIKM as the next stop after a sibling rejection is normal community practice — but only after the prior reviews are actually absorbed. A resubmission with untouched weaknesses will meet a reviewer pool that overlaps heavily with the one that wrote those reviews.

Sibling contrast table